How do I convert a Raster file to COG (Cloud optimised Geotiff) with 4 bands (R,G,B,Alpha)?

I am using FME 2021 and COG was not yet an option in that version.

So I downloaded GDAL COG library and do these conversions with that library, within FME.

import fme
import fmeobjects
import subprocess
import os
import mimetypes

class FeatureProcessor(object):
    def __init__(self):
        print("Initialise Python GDAL Conversion Library")
        # Path to folder containing GDAL
        gdal_folder = FME_MacroValues['GdalDir']
        os.environ["GDAL_DATA"] = os.path.join(gdal_folder, 'data')
        self.gdal_translate = os.path.join(gdal_folder, "bin", "gdal_translate.exe")

        options_cog_with_alpha = ["-of","COG" ,
          "-co","BIGTIFF=YES",
          "-co","COMPRESS=JPEG", 
          "-co","QUALITY=90",
          "-co","BLOCKSIZE=512" ,
          "-co","OVERVIEWS=IGNORE_EXISTING"]

    def input(self, feature):
        print("Start Feature Conversion with GDAL to COG")

        file_dir = feature.getAttribute("LocalWorkDir")
        input_filename = feature.getAttribute("LocalFileName")
        output_folder = 'Converted'
        output_filename = feature.getAttribute("NewLocalFileName") + ".tif"

        input_file = os.path.join(file_dir, input_filename)
        output_file = os.path.join(file_dir, output_folder, output_filename)

        # Check if output directory exits, else create it
        if not os.path.exists(os.path.join(file_dir, output_folder)):
            print("Creating directory:", os.path.join(file_dir, output_folder))
            os.makedirs(os.path.join(file_dir, output_folder))

        print("Converting file:", input_file)
        print("to location:", output_file)

        # Run GDAL Translate to convert to COG
        subprocess.run([self.gdal_translate] + self.options_cog_with_alpha + [input_file, output_file])

        # Set MIME type attribute for the output file
        feature.setAttribute("ContentType", "image/tiff")

        print("Conversion to COG completed.")
        self.pyoutput(feature)

    def close(self):
        pass

I had AI strip the code to the bare basics. But this is an example of using the External GDAL Lib.

At start I used the GDAL Python module, but that did not have the functions I wanted to use.

import fme
import fmeobjects
import subprocess
import os
import mimetypes

class FeatureProcessor(object):
    def __init__(self):
        print("Initialise Python GDAL Conversion Library")
        # Path to folder containing GDAL
        gdal_folder = FME_MacroValues['GdalDir']
        os.environ["GDAL_DATA"] = os.path.join(gdal_folder, 'data')
        self.gdal_translate = os.path.join(gdal_folder, "bin", "gdal_translate.exe")

        options_cog_with_alpha = ["-of","COG" ,
          "-co","BIGTIFF=YES",
          "-co","COMPRESS=JPEG", 
          "-co","QUALITY=90",
          "-co","BLOCKSIZE=512" ,
          "-co","OVERVIEWS=IGNORE_EXISTING"]

    def input(self, feature):
        print("Start Feature Conversion with GDAL to COG")

        file_dir = feature.getAttribute("LocalWorkDir")
        input_filename = feature.getAttribute("LocalFileName")
        output_folder = 'Converted'
        output_filename = feature.getAttribute("NewLocalFileName") + ".tif"

        input_file = os.path.join(file_dir, input_filename)
        output_file = os.path.join(file_dir, output_folder, output_filename)

        # Check if output directory exits, else create it
        if not os.path.exists(os.path.join(file_dir, output_folder)):
            print("Creating directory:", os.path.join(file_dir, output_folder))
            os.makedirs(os.path.join(file_dir, output_folder))

        print("Converting file:", input_file)
        print("to location:", output_file)

        # Run GDAL Translate to convert to COG
        subprocess.run([self.gdal_translate] + self.options_cog_with_alpha + [input_file, output_file])

        # Set MIME type attribute for the output file
        feature.setAttribute("ContentType", "image/tiff")

        print("Conversion to COG completed.")
        self.pyoutput(feature)

    def close(self):
        pass

Thanks for your response.

I have tried to use your code and I also tried to use my code with GDAL lib, but both of them don’t work as expected. It just has 3 bands without Alpha band.

Perhaps COG doesn’t have the function for converting alpha band with compression JPEG.

I want to use COG on my geoserver to remove the black border after georeferencing RASTER with the smallest size.

Do you have any suggestions for me?

Maybe try LERC compression?

I tried all of compression and I found that JPEG is the best compression in my case.

All remaining methods produce results with large capacity